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Bioinformatics Advance Access originally published online on November 14, 2007
Bioinformatics 2008 24(1):135-136; doi:10.1093/bioinformatics/btm535
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R

Nicola Lama 1,* and Mark Girolami 2

1Medical Statistics Unit, Department of Medicine and Public Health, Second University of Napoli, Italy and 2Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, Scotland, UK

*To whom correspondence should be addressed.


  Abstract

Summary: vbmp is an R package for Gaussian Process classification of data over multiple classes. It features multinomial probit regression with Gaussian Process priors and estimates class posterior probabilities employing fast variational approximations to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination. Being equipped with only one main function and reasonable default values for optional parameters, vbmp combines flexibility with ease of usage as is demonstrated on a breast cancer microarray study.

Availability: The R library vbmp implementing this method is part of Bioconductor and can be downloaded from http://www.dcs.gla.ac.uk/~girolami

Contact: nicola.lama{at}unina2.it

Supplementary information: Supplementary data are available at http://www.dcs.gla.ac.uk/~girolami

Associate Editor: Trey Ideker

Received on August 24, 2007; revised on August 24, 2007; accepted on October 16, 2007

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